Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

published:12 Oct 2013

views:166525

"oh, you don't need to guv. it's all in a days work for... bicycle repair man!"

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. It also includes automated linearization of the resulting non-linear models. The software can be used to solve basic physics problems or very complicated many-body and many-constraint systems all with symbolic results. I will go over the basic software design, demonstrate its use through the API along with several classic physics problems and some not-so-trivial three dimensional multi-body problems.

published:02 Jul 2013

views:3833

Brief description of the Object Oriented Mechanics Library and a short demo of the implementation in python (Pyooml)
https://github.com/Obijuan/pyooml
http://iearobotics.com/oomlwiki/doku.php?id=start

published:19 Oct 2012

views:1106

A family in Zimbabwe discovered that a giant python under the hood of their truck was the source of their engine trouble.

In roller coasters

Python (Coney Island), a D.P.V. Rides designed Zyklon-style steel roller coaster that operated from 1996 to 1999 at Splash Zone Water Park but was relocated to Coney Island at the end of the 1999 season

Python (genus)

Python, from the Greek word (πύθων/πύθωνας), is a genus of nonvenomous pythons found in Africa and Asia. Currently, 12 species are recognised. A member of this genus, P. reticulatus, is among the longest snake species and extant reptiles in the world.

Some suggest that P. molurus and P. sebae have the potential to be problematic invasive species in South Florida. The United States Department of Agriculture reports that only Python molurus bivittatus is an invasive species in the United States. More recent data suggest that these pythons would not withstand winter climates north of Florida, contradicting previous research suggesting a more significant geographic potential range.

Python (Busch Gardens Tampa Bay)

Python was a steel corkscrew roller coaster at Busch Gardens Tampa Bay in Tampa. Built by Arrow Development in 1976 and opened on July 1, 1976, it was the first roller coaster since the park's opening in 1959. The ride was located in the Congo section of the park near Stanley Falls Flume and Congo River Rapids.

The ride received a repaint in 2003, the trains were also painted with the park's current logo, switched from the classic Python logo.

Python was permanently closed on October 31, 2006, and demolished for scrap shortly after. The removal of Python was necessary to make way for the park's Jungala attraction, and was part of the largest renovation in Busch Gardens' history.

Along with Python, the area's Tiger's Den gift shop, and Python Soft Serve have been torn down as a part of the Congo renovation.

Layout

Python was a stock model roller coaster made by Arrow Dynamics, which was a clone of Knott's Berry Farm's now defunct Corkscrew roller coaster (which now operates at Silverwood amusement park in Athol, Idaho).

Monty Python

Monty Python (sometimes known as The Pythons) were a Britishsurreal comedy group who created the sketch comedy show Monty Python's Flying Circus, that first aired on the BBC on 5 October 1969. Forty-five episodes were made over four seasons. The Python phenomenon developed from the television series into something larger in scope and impact, spawning touring stage shows, films, numerous albums, several books, and a stage musical. The group's influence on comedy has been compared to The Beatles' influence on music.

Broadcast by the BBC between 1969 and 1974, Flying Circus was conceived, written, and performed by its members Graham Chapman, John Cleese, Terry Gilliam, Eric Idle, Terry Jones, and Michael Palin. Loosely structured as a sketch show, but with an innovative stream-of-consciousness approach (aided by Gilliam's animation), it pushed the boundaries of what was acceptable in style and content. A self-contained comedy team responsible for both writing and performing their work, the Pythons had creative control which allowed them to experiment with form and content, discarding rules of television comedy. Their influence on British comedy has been apparent for years, while in North America, it has coloured the work of cult performers from the early editions of Saturday Night Live through to more recent absurdist trends in television comedy. "Pythonesque" has entered the English lexicon as a result.

Monty Python Bicycle Repairman

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

4:05

Monty Python FC 3. - Biciklijavító (Bicycle Repair Man)

Monty Python FC 3. - Biciklijavító (Bicycle Repair Man)

Monty Python FC 3. - Biciklijavító (Bicycle Repair Man)

"oh, you don't need to guv. it's all in a days work for... bicycle repair man!"

How to: Random Dot Mechanic Python

Dynamics with SymPy Mechanics; SciPy 2013 Presentation

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. It also includes automated linearization of the resulting non-linear models. The software can be used to solve basic physics problems or very complicated many-body and many-constraint systems all with symbolic results. I will go over the basic software design, demonstrate its use through the API along with several classic physics problems and some not-so-trivial three dimensional multi-body problems.

3:13

Pyooml: Object oriented Mechanics in python (in Enghlish)

Pyooml: Object oriented Mechanics in python (in Enghlish)

Pyooml: Object oriented Mechanics in python (in Enghlish)

Brief description of the Object Oriented Mechanics Library and a short demo of the implementation in python (Pyooml)
https://github.com/Obijuan/pyooml
http://iearobotics.com/oomlwiki/doku.php?id=start

1:06

Giant python discovered under truck's hood

Giant python discovered under truck's hood

Giant python discovered under truck's hood

A family in Zimbabwe discovered that a giant python under the hood of their truck was the source of their engine trouble.

12:03

Python and SEO in NYC 2017

Python and SEO in NYC 2017

Python and SEO in NYC 2017

21:36

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural network architecture, or feature engineering, they will most probably say cleaning and shaping data. The struggle to work with messy data is what can make or break a project and sometimes hide the real gems the data has to show us. Many junior data practitioners shrug off this stage as mechanic and boring, and tend to put little thought towards it. It turns out that there is a "right" way to tidy data that allows for easy analysis and visualization down the line Tidy data has a specific structure, which can be summarized in two sentences: each variable is a column; each observation is a row. The simplicity of this strategy makes it easy to understand how to tidy data, and only requires a small set of tools to deal with a wide range of messy datasets. These tools have been developed in the popular r packages dplyr and tidyr. Alas, this is not an r conference, and we are but hapless python developers. Is our fate to be left out in the cold with all our messy data?!? Not on my watch! In this talk we will learn about "tidy data", a strategy formulated by Hadley Wickham in 2014. We will also go over common cases of messy data and how to tidy them with python tools, and we will see how using this system we can quickly achieve complex analyses and intuitive visualizations.
Relevant article and blog posts:
http://jalammar.github.io/visualizing-pandas-pivoting-and-reshaping/
http://www.jeannicholashould.com/tidy-data-in-python.html
https://www.jstatsoft.org/article/view/v059i10

1:59

Meet Mechanical Engineers at Google

Meet Mechanical Engineers at Google

Meet Mechanical Engineers at Google

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-paced manufacturing and product oriented development environment. Learn about their team culture, work, and what makes hardware engineering at Google so exciting.
Learn more about mechanical engineering at Google and check out open jobs → https://goo.gl/fA3jfr
Subscribe to Life at Google for more videos → https://goo.gl/kqwUZd
Follow us!
Twitter: https://goo.gl/kdYxFP
Facebook: https://goo.gl/hXDzLf
Google Plus: https://goo.gl/YBcMZK
#LifeAtGoogle

Monty Python Bicycle Repairman

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

published: 11 Feb 2013

Monty Python - Mechanik Rowerowy

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

published: 12 Oct 2013

Monty Python FC 3. - Biciklijavító (Bicycle Repair Man)

"oh, you don't need to guv. it's all in a days work for... bicycle repair man!"

How to: Random Dot Mechanic Python

Dynamics with SymPy Mechanics; SciPy 2013 Presentation

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. ...

published: 02 Jul 2013

Pyooml: Object oriented Mechanics in python (in Enghlish)

Brief description of the Object Oriented Mechanics Library and a short demo of the implementation in python (Pyooml)
https://github.com/Obijuan/pyooml
http://iearobotics.com/oomlwiki/doku.php?id=start

published: 19 Oct 2012

Giant python discovered under truck's hood

A family in Zimbabwe discovered that a giant python under the hood of their truck was the source of their engine trouble.

published: 07 Mar 2016

Python and SEO in NYC 2017

published: 12 Jul 2017

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural network architecture, or feature engineering, they will most probably say cleaning and shaping data. The struggle to work with messy data is what can make or break a project and sometimes hide the real gems the data has to show us. Many junior data practitioners shrug off this stage as mechanic and boring, and tend to put little thought towards it. It turns out that there is a "right" way to tidy data that allows for easy analysis and visualization down the line Tidy data has a specific structure, which can be summarized in two sentences: each variable is a column; each observation is a row. The simplicity of this strategy makes it ...

published: 10 Jul 2018

Meet Mechanical Engineers at Google

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-paced manufacturing and product oriented development environment. Learn about their team culture, work, and what makes hardware engineering at Google so exciting.
Learn more about mechanical engineering at Google and check out open jobs → https://goo.gl/fA3jfr
Subscribe to Life at Google for more videos → https://goo.gl/kqwUZd
Follow us!
Twitter: https://goo.gl/kdYxFP
Facebook: https://goo.gl/hXDzLf
Google Plus: https://goo.gl/YBcMZK
#LifeAtGoogle

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some a...

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. It also includes automated linearization of the resulting non-linear models. The software can be used to solve basic physics problems or very complicated many-body and many-constraint systems all with symbolic results. I will go over the basic software design, demonstrate its use through the API along with several classic physics problems and some not-so-trivial three dimensional multi-body problems.

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. It also includes automated linearization of the resulting non-linear models. The software can be used to solve basic physics problems or very complicated many-body and many-constraint systems all with symbolic results. I will go over the basic software design, demonstrate its use through the API along with several classic physics problems and some not-so-trivial three dimensional multi-body problems.

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural ...

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural network architecture, or feature engineering, they will most probably say cleaning and shaping data. The struggle to work with messy data is what can make or break a project and sometimes hide the real gems the data has to show us. Many junior data practitioners shrug off this stage as mechanic and boring, and tend to put little thought towards it. It turns out that there is a "right" way to tidy data that allows for easy analysis and visualization down the line Tidy data has a specific structure, which can be summarized in two sentences: each variable is a column; each observation is a row. The simplicity of this strategy makes it easy to understand how to tidy data, and only requires a small set of tools to deal with a wide range of messy datasets. These tools have been developed in the popular r packages dplyr and tidyr. Alas, this is not an r conference, and we are but hapless python developers. Is our fate to be left out in the cold with all our messy data?!? Not on my watch! In this talk we will learn about "tidy data", a strategy formulated by Hadley Wickham in 2014. We will also go over common cases of messy data and how to tidy them with python tools, and we will see how using this system we can quickly achieve complex analyses and intuitive visualizations.
Relevant article and blog posts:
http://jalammar.github.io/visualizing-pandas-pivoting-and-reshaping/
http://www.jeannicholashould.com/tidy-data-in-python.html
https://www.jstatsoft.org/article/view/v059i10

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural network architecture, or feature engineering, they will most probably say cleaning and shaping data. The struggle to work with messy data is what can make or break a project and sometimes hide the real gems the data has to show us. Many junior data practitioners shrug off this stage as mechanic and boring, and tend to put little thought towards it. It turns out that there is a "right" way to tidy data that allows for easy analysis and visualization down the line Tidy data has a specific structure, which can be summarized in two sentences: each variable is a column; each observation is a row. The simplicity of this strategy makes it easy to understand how to tidy data, and only requires a small set of tools to deal with a wide range of messy datasets. These tools have been developed in the popular r packages dplyr and tidyr. Alas, this is not an r conference, and we are but hapless python developers. Is our fate to be left out in the cold with all our messy data?!? Not on my watch! In this talk we will learn about "tidy data", a strategy formulated by Hadley Wickham in 2014. We will also go over common cases of messy data and how to tidy them with python tools, and we will see how using this system we can quickly achieve complex analyses and intuitive visualizations.
Relevant article and blog posts:
http://jalammar.github.io/visualizing-pandas-pivoting-and-reshaping/
http://www.jeannicholashould.com/tidy-data-in-python.html
https://www.jstatsoft.org/article/view/v059i10

Meet Mechanical Engineers at Google

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-pace...

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-paced manufacturing and product oriented development environment. Learn about their team culture, work, and what makes hardware engineering at Google so exciting.
Learn more about mechanical engineering at Google and check out open jobs → https://goo.gl/fA3jfr
Subscribe to Life at Google for more videos → https://goo.gl/kqwUZd
Follow us!
Twitter: https://goo.gl/kdYxFP
Facebook: https://goo.gl/hXDzLf
Google Plus: https://goo.gl/YBcMZK
#LifeAtGoogle

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-paced manufacturing and product oriented development environment. Learn about their team culture, work, and what makes hardware engineering at Google so exciting.
Learn more about mechanical engineering at Google and check out open jobs → https://goo.gl/fA3jfr
Subscribe to Life at Google for more videos → https://goo.gl/kqwUZd
Follow us!
Twitter: https://goo.gl/kdYxFP
Facebook: https://goo.gl/hXDzLf
Google Plus: https://goo.gl/YBcMZK
#LifeAtGoogle

Dan, Mechanical Engineer at Tesla Motors: Advice to Engineering Students

Like http://www.facebook.com/staywithitengineering for more advice.
Dan, a mechanical engineer working at Tesla Motors in the Powertrain Test Lab, shares some advice to current engineering students at University of Florida as a part of the STAY WITH IT speaker series. http://www.staywithit.org

Welcome to the MachineLearning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.
The file: http://sentdex.com/GBPUSD.zip
This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.
Sentdex.com
Facebook.com/sentdex
Twitter.com/sentdex

Dynamics with SymPy Mechanics; SciPy 2013 Presentation

Authors: Moore, Jason, University of California at DavisTrack: General
The SymPy Mechanics package was created to automate the derivation of the equations of motion for rigid body dynamics problems. It has been developed primarily through several Google Summer of Code grants over three years and is capable of deriving Newton's Second Law for non-trivial multi-body systems using a variety of methods: from Newton-Euler, to Lagrange, to Kane. The software provides essential classes based around the concepts of a three dimensional vector in a reference frame which ease the setup and bookkeeping of the tedious kinematics including both kinematic and motion constraints. There are also classes for the automated formulation of the equations of motion based on the bodies and forces in a system. It also includes automated linearization of the resulting non-linear models. The software can be used to solve basic physics problems or very complicated many-body and many-constraint systems all with symbolic results. I will go over the basic software design, demonstrate its use through the API along with several classic physics problems and some not-so-trivial three dimensional multi-body problems.

Tidy Data in Python - Aviv Rotman - PyCon Israel 2018

If you ask any data scientist what is the most frustrating and time consuming part of a data science project, surprisingly they won't say visualization, neural network architecture, or feature engineering, they will most probably say cleaning and shaping data. The struggle to work with messy data is what can make or break a project and sometimes hide the real gems the data has to show us. Many junior data practitioners shrug off this stage as mechanic and boring, and tend to put little thought towards it. It turns out that there is a "right" way to tidy data that allows for easy analysis and visualization down the line Tidy data has a specific structure, which can be summarized in two sentences: each variable is a column; each observation is a row. The simplicity of this strategy makes it easy to understand how to tidy data, and only requires a small set of tools to deal with a wide range of messy datasets. These tools have been developed in the popular r packages dplyr and tidyr. Alas, this is not an r conference, and we are but hapless python developers. Is our fate to be left out in the cold with all our messy data?!? Not on my watch! In this talk we will learn about "tidy data", a strategy formulated by Hadley Wickham in 2014. We will also go over common cases of messy data and how to tidy them with python tools, and we will see how using this system we can quickly achieve complex analyses and intuitive visualizations.
Relevant article and blog posts:
http://jalammar.github.io/visualizing-pandas-pivoting-and-reshaping/
http://www.jeannicholashould.com/tidy-data-in-python.html
https://www.jstatsoft.org/article/view/v059i10

Meet Mechanical Engineers at Google

Meet some of our Mechanical Engineers who participate in the design, analysis, and prototyping of new concepts. They're developing new technology in a fast-paced manufacturing and product oriented development environment. Learn about their team culture, work, and what makes hardware engineering at Google so exciting.
Learn more about mechanical engineering at Google and check out open jobs → https://goo.gl/fA3jfr
Subscribe to Life at Google for more videos → https://goo.gl/kqwUZd
Follow us!
Twitter: https://goo.gl/kdYxFP
Facebook: https://goo.gl/hXDzLf
Google Plus: https://goo.gl/YBcMZK
#LifeAtGoogle

In roller coasters

Python (Coney Island), a D.P.V. Rides designed Zyklon-style steel roller coaster that operated from 1996 to 1999 at Splash Zone Water Park but was relocated to Coney Island at the end of the 1999 season